autoscaling with magnum and senlin

1

Exploring Magnum and Senlin integration

for autoscaling containers

Hongbin Lu (Huawei)

Jay Lau, Ton Ngo (IBM)

Qiming Teng, Julio Ruano (IBM)

Exploring Magnum and Senlin integration

Contributors

Exploring Magnum and Senlin integration 2

Zilian Ji, Linjuan Xia, Shijia E, Peiyu Lin, Tianyuan Zhuang, Ji Jiang, Yongkui Wang

Talk Outline

1. Use cases

2. Magnum

3. Senlin

4. How it works

5. Demo

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Use cases

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Use case

• Shared COE cluster

– Autoscale on some policies (utilization, etc.)

– Scale number of nodes

• Multiple apps on cluster

– Autoscale on some policies (request rate, etc.)

– Scale number of containers

• Example:

– 2, 3-tiered web apps: handle requests

– SLA determines policy

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Scaling scenarios (1)

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node

c c c

node

c cc

node

c scale app

scale cluster

Single app on cluster

• scale out containers as needed

• scale cluster by utilization

• coordination = utilization

Scaling scenarios (2)

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node

c

node

c c

node

c c c c scale 2 apps

Two apps on cluster

• scale out containers as needed

• scale cluster by utilization

• coordination = utilization

scale cluster

unlimited

scale cluster

limited

Scaling scenarios (3)

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node

c c

node

scale 2 apps

scale cluster

limited

c

node

c c c c c c

Two apps on cluster, limited cluster size

• blue scales first, retains containers

• red scales later, fails

• maybe acceptable

• what if red is critical and blue is not

• inverted priority: blue < red

Scaling scenarios (4)

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node

c c scale 2 apps

Limit on apps

• Place max on blue

• blue scales, red does not scale

• cannot use full resources

scale cluster

limited

c

nodenode

c

limited

Scaling scenarios (5)

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node

c c

node

scale 2 apps

scale cluster

limited

c

node

c c c c c cc c c c

Priority on apps

• blue scales first, red scales later

• blue scales back to free up resource for red

• 2 ways linkage: container cluster host cluster

Magnum

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Instance

Magnum Overview

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• Provision

• Kubernetes

• Docker Swarm

• Mesos

• Scale

• Add instances

• Remove instances

• Manage

• Pod

• Service

• Replication Controller

• Container

Nova Instance

containercontainer

Magnum CLI

Magnum

Heat

Magnum Architecture

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Magnum: Autoscale Bay

1. Raw data: Magnum pulls raw

data from Bays.

2. Metrics: Metrics, like memory

utilization, are computed and sent

them to Ceilometer.

3. Alarm: Ceilometer triggers alarms

based on user-specified scenario

and metrics.

4. Scale: Heat scales the bays.

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Ceilometer

Magnum Heat

Bay1) Raw data

2) Metrics 3) Alarm

4) Scale

Kubernetes: Autoscale Pod

1. Metrics: The autoscaler

periodically queries pods’ metrics.

2. Scale: Based on collected

metrics, the autoscaler uses a

built-in algorithm to trigger the

scaling.

3. Resize: Replication Controller

resize the pods.

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Horizontal

Pod

Autoscaler

Pods

1) Metrics3) Resize

Replication

Controller

2) Scale

Future direction

• Magnum AutoScaler

– A new component in Magnum

• Scaling Bays

• Scaling Applications

– Interacts with AutoScaler from COEs

• Kubernetes AutoScaler as a driver for container-level scaling

• Magnum responsible for scaling RCs without Kubernetes autoscaler

– Customizability

• data sources

• metrics and thresholds

• standby bay nodes (i.e. resource pool)

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Two-Levels of AutoScaling

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Working

K8S Bay

NodeNode

K8S Master

Heapster

Kublet

cAdvisor

Kublet

cAdvisor

Storage Backend

RC AutoScaler

Pod

Magnum AutoScaler Service

K8S Driver

Collector

Analyzer

OperatorSwarm Driver

MesosDriver

Senlin

Magnum Conductor

Standby

Senlin

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Clustering - A Missing Service in OpenStack

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Scalable

Load-Balanced

Highly-Available

Manageable

......

of any (OpenStack) objects

Senlin Architecture

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REST RPC

Senlin

Database

Policies

Profiles

Clustering/AutoScaling/LoadBalancing

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Nova

Kubernetes

Heat

Ironic BareMetal

VMs

Stacks

Containers

Senlin

placement

deletion

scaling

health

load-balance

batching

Scaling A Cluster using Senlin

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type: os.nova.serverversion: 1.0properties:

image: fedora-21flavor: 3networks:

- network: privateuserdata:

...

Profile

Cluster

type: senlin.policy.scalingversion: 1.0properties:

event: CLUSTER_SCALE_INadjustment:

type: CHANGE_IN_CAPACITYnumber: 1min_step: 1best_effort: True

attach

Policy

type: senlin.policy.scalingversion: 1.0properties:

event: CLUSTER_SCALE_OUTadjustment:

. . .

attach

Policy

webhook

RESIZE

Policies

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type: senlin.policy.scalingversion: 1.0properties:adjustment:min_step: 1

best_effort: true

number: 1type: CHANGE_IN_CAPACITY

event: CLUSTER_SCALE_OUT

• Declarative

• Can be mapped to from a standard

• Example: SUR_Cluster

(Add k8s Minion / Add Spark worker node)

Trigger

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type: CeilometerThresholdAlarmversion: 1.0rule:meter_name: memory_utilcomparison_operator: gtthreshold: 70period: 60evaluation_periods: 1statistic: avgquery:- field: resource_metadata.clusterop: eqvalue: SUR_Cluster

• Generic abstraction

• alarms in OpenStack

monitoring services

• e.g. Ceilometer Alarm

How it works

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Design goals

1. Coordinate scaling at apps and cluster level

• Control flows in both direction

• Apps -> Cluster: utilization, other methods

• Cluster -> Apps: priority, other methods

2. Integrate scaling support from COE if available

• Kubernetes autoscaler

3. Policy driven

• Easy to express, manage complex cases

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template

Outer Stack

Autoscaling: OpenStack-Only Solution (Today)

27 Exploring Magnum and Senlin integration

AutoScalingGroup Stack

Heat

Ceilometer

AH

PUp PDn

AL

ASGS1 S2 S3

updateASG

Senlin

profile

Autoscaling: OpenStack-Only Solution (New)

28 Exploring Magnum and Senlin integration

Cluster

Ceilometer

AH

PUp

PDn

AL

SCALE_IN

SCALE_OUT

Node1 Node2 Node3

webhookspolicies triggers

Demo

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Autoscaling with Kubernetes

30 Exploring Magnum and Senlin integration

VMs

K8S Bay

NodeNode

Heapster

Kublet

cAdvisor

Kublet

cAdvisor

Pod

Senlin

Magnum

profile

CeilometerWorkload

policy

Questions

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Thank You

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